MCA-105 Computer Oriented Numerical And Statistical Methods Using C !

Computer Arithmetic: Floating-point representation of numbers, arithmetic operations with normalized floating point numbers and their consequences. Error in number representation – pitfalls in computing.

Iterative Methods: Bisection, False position, Newton-Raphson methods, Discussion of convergences, Graeffe’s root squareing method and Bairstow’s Method.

Solving of Simultaneous Linear Equations and ordinary Differential Equations: Gauss elimination method, Ill-conditioned equations, Gauss-Seidal iterative method, Euler’s Modified Method, Taylors series and Euler methods, Runga-kutta methods, Predictor corrector methods.

Numerical Differentiation and Integration: Differentiation formulae based on polynomial fit, Pitfalls in differentiation, Trapezoidal, Simpson’s rules and Gaussian Quadrature.

Interpolation and Approximation: Polynomial interpolation, Difference tables, Inverse interpolation, Polynomial fitting and other curve fitting. Approximation of functions by Taylor series and Chebyshev polynomials.

Statistical methods: Sample distributions, Test of Significance, n2, t and F test.

Analysis of Variance: Definition, Assumptions, Cochran’s Theorem(only statement), One-way classification, ANOVA Table, Two-way classification (with one observation per cell).

Time Series Analysis: Components and Analysis of Time Series, Measurement of Trend, Seasonal fluctuations and Cyclic movement.

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